A Branch-and-Bound Method for the Optimal Scheduling

This paper presents a new approach to the scheduling problem in high level synthesis. In this approach, iterative rescheduling processes are performed in a branch-andbound manner, starting with the as soon as possible scheduling result, so as to find the scheduling result of the lowest hardware cost under the given timing constraint. At each iteration step, only the candidate nodes are selected to be considered for rescheduling and the lower bound estimation is performed so as to help increase the number of cut-offs in the search space, and thus reducing the run time. Our algorithm also supports mutually exclusive operations, multiple operations per cycle, multi-cycling operations, and pipelined data paths. Experimental results are given to show that our algorithm derives an optimal scheduling result within a reasonably short CPU time.